Revenue Management
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Revenue Management aims to maximize revenue growth by selling the right product to the right customer at the right time for the right price. It uses data-driven tactics and strategy to determine what to sell, when to sell, to whom to sell, and for how much. The key levers of Revenue Management include pricing, inventory, marketing, and channels. The Revenue Management process begins with data collection, then proceeds to segmentation, forecasting, optimization, and dynamic re-evaluation.
![Revenue Management
Revenue Management is the application of disciplined analytics that predict consumer behavior at
the micro-market level and optimize product availability and price to maximize revenue growth. The
primary aim of Revenue Management is selling the right product to the right customer at the right time
for the right price and with the right pack. The essence of this discipline is in understanding customers'
perception of product value and accurately aligning product prices, placement and availability with
each customer segment.
Overview
Businesses face important decisions regarding what to sell, when to sell, to whom to sell, and for how
much. Revenue Management uses data-driven tactics and strategy to answer these questions in order
to increase revenue.[2]
The discipline of revenue management combines data mining and operations
research with strategy, understanding of customer behavior, and partnering with the sales force.
Today, the revenue management practitioner must be analytical and detail oriented, yet capable of
thinking strategically and managing the relationship with sales
The Revenue Management Levers
Whereas yield management involves specific actions to generate yield through perishable inventory
management, Revenue Management encompasses a wide range of opportunities to increase revenue.
A company can utilize these different categories like a series of levers in the sense that all are usually
available, but only one or two may drive revenue in a given situation. The primary levers are:
Pricing
This category of Revenue Management involves redefining pricing strategy and developing
disciplined pricing tactics. The key objective of a pricing strategy is anticipating the value created for
customers and then setting specific prices to capture that value. A company may decide to price
against their competitors or even their own products, but the most value comes from pricing strategies
that closely follow market conditions and demand, especially at a segment level. Once a pricing
strategy dictates what a company wants to do, pricing tactics determine how a company actually
captures the value. Tactics involve creating pricing tools that change dynamically, in order to react to
changes and continually capture value and gain revenue. Price Optimization, for example, involves
constantly optimizing multiple variables such as price sensitivity, price ratios, and inventory to
maximize revenues. A successful pricing strategy, supported by analytically-based pricing tactics, can
drastically improve a firm’s profitability.[21]
Inventory
When focused on controlling inventory, Revenue Management is mainly concerned with how best to
price or allocate capacity. First, a company can discount products in order to increase volume. By
lowering prices on products, a company can overcome weak demand and gain market share, which
ultimately increases revenue so long as each product sells for more than its marginal cost. On the other
hand, in situations where demand is strong for a product but the threat of cancellations looms (e.g.
hotel rooms or airline seats), firms often overbook in order to maximize revenue from full
capacity. Overbooking’s focus is increasing the total volume of sales in the presence of cancellations
rather than optimizing customer mix.
Marketing
Price promotion allow companies to sell higher volumes by temporarily decreasing the price of their
products. Revenue Management techniques measure customer responsiveness to promotions in order](https://image.slidesharecdn.com/4c5cab5d-96fb-4476-b14a-c4bea577eed3-150518111220-lva1-app6892/85/Revenue-Management-1-320.jpg)
![to strike a balance between volume growth and profitability. An effective promotion helps maximize
revenue when there is uncertainty about the distribution of customer willingness to pay. When a
company’s products are sold in the form of long-term commitments, such as internet or telephone
service, promotions help attract customers who willthen commit to contracts and produce revenue
over a long time horizon. When this occurs, companies must also strategize their promotion roll-off
policies; they must decide when to begin increasing the contract fees and by what magnitude to raise
the fees in order to avoid losing customers. Revenue Management optimization proves useful in
balancing promotion roll-off variables in order to maximize revenue while minimizing churn.
Channels
Revenue Management through channels involves strategically driving revenue through
different distribution channels. Different channels may represent customers with different price
sensitivities. For example, customers who shop online are usually more price sensitive than customers
who shop in a physical store. Different channels often have different costs and margins associated
with those channels. When faced with multiple channels to retailers and distributors, Revenue
Management techniques can calculate appropriate levels of discounts for companies to offer
distributors through opaque channels to push more products without losing integrity with respect to
public perception of quality.
The Revenue Management Process
Data Collection
The Revenue Management process begins with data collection. Relevant data is paramount to a
Revenue Management System’s capability to provide accurate, actionable information. A system must
collect and store historical data for inventory, prices, demand, and other causal factors. Any data that
reflects the details of products offered, their prices, competition, and customer behavior must be
collected, stored, and analyzed. In some markets, specialized data collection methods have rapidly
emerged to service their relevant sector, and sometimes have even become a norm. In the European
Union for example, the European Commission makes sure businesses and governments stick to EU
rules on fair competition, while still leaving space for innovation, unified standards, and the
development of small businesses. To support this, third party sources are utilized to collect data and
make only averages available for commercialpurposes, such as is the case with the hotel sector – in
Europe [23]
and the Middle East & North Africa region,[24]
where key operating indicators are
monitored, such as Occupancy Rate (OR), Average Daily Rate (ADR) and Revenue per Available
Room (RevPAR). Data is supplied directly by hotel chains and groups (as well as independent
properties) and benchmark averages are produced by direct market (competitive set) or wider macro
market. This data is also utilized for financial reporting, forecasting trends and development purposes.
Information about customer behavior is a valuable asset that can reveal consumer behavioral patterns,
the impact of competitors’ actions, and other important market information. This information is
crucial to starting the Revenue Management process.
Segmentation
After collecting the relevant data, market segmentation is the key to market-based pricing and revenue
maximization. Success hinges on the ability to segment customers into similar groups based on a
calculation of price responsiveness of customers to certain products based upon the circumstances of
time and place. Revenue Management strives to determine the value of a product to a very narrow
micro-market at a specific moment in time and then chart customer behavior at the margin to
determine the maximum obtainable revenue from those micro-markets.[1]
Useful tools such as Cluster
Analysis allow Revenue Managers to create a set of data-driven partitioning techniques that gather
interpretable groups of objects together for consideration. Market segmentation based upon customer
behavior is essential to the next step, which is forecasting demand associated with the clustered
segments.](https://image.slidesharecdn.com/4c5cab5d-96fb-4476-b14a-c4bea577eed3-150518111220-lva1-app6892/85/Revenue-Management-2-320.jpg)
![Forecasting
Revenue Management requires forecasting various elements such as demand, inventory
availability, market share, and total market. Its performance depends critically on the quality of these
forecasts. Forecasting is a critical task of Revenue Management and takes much time to develop,
maintain, and implement. Quantity-based forecasts, which use time-series models, booking curves,
cancellation curves, etc., project future quantities of demand, such as reservations or products bought.
Price-based forecasts seek to forecast demand as a function of marketing variables, such as price or
promotion. These involve building specialized forecasts such as market response models or cross-
price elasticity estimates to predict customer behavior at certain price points. By combining these
forecasts with calculated price sensitivities and price ratios, a Revenue Management System can then
quantify these benefits and develop price optimization strategies to maximize revenue.
Optimization
While forecasting suggests what customers are likely to do, optimization suggests how a firm should
respond. Often considered the pinnacle of the Revenue Management process, optimization is about
evaluating multiple options on how to sell your product and to whom to sell your
product.[1]
Optimization involves solving two important problems in order to achieve the highest
possible revenue. The first is determining which objective function to optimize. A business must
decide between optimizing prices, total sales, contribution margins, or even customer lifetime values.
Secondly, the business must decide which optimization technique to utilize. For example, many firms
utilize linear programming, a complex technique for determining the best outcome from a set of linear
relationships, to set prices in order to maximize revenue. Regression analysis, another statistical tool,
involves finding the ideal relationship between several variables through complex models and
analysis. Discrete choice models can serve to predict customer behavior in order to target them with
the right products for the right price. Tools such as these allow a firm to optimize its product offerings,
inventory levels, and pricing points in order to achieve the highest revenue possible.
Dynamic Re-evaluation
Revenue Management requires that a firm must continually re-evaluate their prices, products, and
processes in order to maximize revenue. In a dynamic market, an effective Revenue Management
System constantly re-evaluates the variables involved in order to move dynamically with the market.
As micro-markets evolve, so must the strategy and tactics of Revenue Management adjust.
Revenue Management in an Organization
Revenue Management’s fit within the organizational structure depends on the type of industry and the
company itself. Some companies place Revenue Management teams within Marketing because
marketing initiatives typically focus on attracting and selling to customers. Other firms dedicate a
section of Finance to handle Revenue Management responsibilities because of the tremendous bottom
line implications. Some companies have elevated the position of Chief Revenue Officer, or CRO, to
the senior management level. This position typically oversees functions like sales, pricing, new
product development, and advertising and promotions. A CRO in this sense would be responsible for
all activities that generate revenue and directing the company to become more “revenue-focused.
Supply Chain Management and Revenue Management have many natural synergies. Supply chain
management (SCM) is a vital process in many companies today and several are integrating this
process with a Revenue Management System. On one hand, supply chain management often focuses
on filling current and anticipated orders at the lowest cost, while assuming that demand is primarily
exogenous. Conversely, Revenue Management generally assumes costs and sometimes capacity are
fixed and instead looks to set prices and customer allocations that maximize revenue given these
constraints. Acompany that has achieved excellence in Supply Chain Management and Revenue](https://image.slidesharecdn.com/4c5cab5d-96fb-4476-b14a-c4bea577eed3-150518111220-lva1-app6892/85/Revenue-Management-3-320.jpg)
![Management individually may have many opportunities to increase profitability by linking their
respective operational focus and customer-facing focus together.
Business Intelligence platforms have also become increasingly integrated with the Revenue
Management process. These platforms, driven by data mining processes, offer a centralized data and
technology environment that delivers business intelligence by combining historical reporting and
advanced analytics to explain and evaluate past events, deliver recommended actions and eventually
optimize decision-making. Not synonymous with Customer Relationship Management (CRM),
Business intelligence generates proactive forecasts, whereas CRM strategies track and document a
company’s current and past interactions with customers. Data mining this CRM information, however,
can help drive a business intelligence platform and provide actionable information to aid decision-
making.
Developing Industries
The ability for Revenue Management to optimize price based on forecasted demand, price elasticity
and competitive rates has incredible benefits, and many companies are rushing to develop their own
Revenue Management capabilities. Many industries are beginning to embrace Revenue Management
and apply its principles to their business processes:
Financial Services – offer a wide range of products to a wide range of customers. Banks have
applied segmented pricing tactics to loan holders, often utilizing heavy amounts of data and
modeling to project interest rates based on how much a customer is willing to pay.[26]
Media/Telecom – a promotion-driven industry often focused on attracting customers with
discounted plans and then retaining them at higher price points. Businesses in this industry often
face regulatory constraints, demand volatility, and sales through multiple channels to both
business and consumer segments. Revenue Management can help these companies understand
micro-markets and forecast demand in order to optimize advertising sales and long-term
contracts.
Distributors – face a complex environment that often includes thousands of individual SKUs with
several different product lifecycles. Each distributor must account for factors such as channel
conflict, cross-product cannibalization, and competitive actions. Revenue Management has
proved useful to distributors in promotion analysis and negotiated contracts.
Medical Products and Services – deal with large fluctuations in demand depending on time of day
and day of week. Hospital surgeries are often overflowing on weekday mornings but sit empty
and underutilized on the weekend. Hospitals may experiment with optimizing their inventory of
services and products based on different demand points. Additionally, Revenue Management
techniques allow hospitals to mitigate claim underpayments and denials, thus preventing
significant revenue leakage.[29]
MKG Group’s HotelCompSet performance indicators in Europe](https://image.slidesharecdn.com/4c5cab5d-96fb-4476-b14a-c4bea577eed3-150518111220-lva1-app6892/85/Revenue-Management-4-320.jpg)
![ Hotel and Hospitality services – daily revenue or yield management strategies are a popular
practice within the hotel sector, particularly prominent in mature and large hotel markets such as
in Western Europe and the North America. Key operating indicators Occupancy Rate (OR),
Average Daily Rate (ADR) and Revenue per Available Room (RevPAR) are tracked using third
party sources to follow direct competitor set averages in demand and price, thereby indicating
penetration rate and performance index.[30]
Wider or macro market averages are also monitored.
Since the hotel industry is cyclic, revenue managers can confidently maneuver supply and
demand statistics to reach optimal results.](https://image.slidesharecdn.com/4c5cab5d-96fb-4476-b14a-c4bea577eed3-150518111220-lva1-app6892/85/Revenue-Management-5-320.jpg)
Revenue Management
- 1. Revenue Management Revenue Management is the application of disciplined analytics that predict consumer behavior at the micro-market level and optimize product availability and price to maximize revenue growth. The primary aim of Revenue Management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment. Overview Businesses face important decisions regarding what to sell, when to sell, to whom to sell, and for how much. Revenue Management uses data-driven tactics and strategy to answer these questions in order to increase revenue.[2] The discipline of revenue management combines data mining and operations research with strategy, understanding of customer behavior, and partnering with the sales force. Today, the revenue management practitioner must be analytical and detail oriented, yet capable of thinking strategically and managing the relationship with sales The Revenue Management Levers Whereas yield management involves specific actions to generate yield through perishable inventory management, Revenue Management encompasses a wide range of opportunities to increase revenue. A company can utilize these different categories like a series of levers in the sense that all are usually available, but only one or two may drive revenue in a given situation. The primary levers are: Pricing This category of Revenue Management involves redefining pricing strategy and developing disciplined pricing tactics. The key objective of a pricing strategy is anticipating the value created for customers and then setting specific prices to capture that value. A company may decide to price against their competitors or even their own products, but the most value comes from pricing strategies that closely follow market conditions and demand, especially at a segment level. Once a pricing strategy dictates what a company wants to do, pricing tactics determine how a company actually captures the value. Tactics involve creating pricing tools that change dynamically, in order to react to changes and continually capture value and gain revenue. Price Optimization, for example, involves constantly optimizing multiple variables such as price sensitivity, price ratios, and inventory to maximize revenues. A successful pricing strategy, supported by analytically-based pricing tactics, can drastically improve a firm’s profitability.[21] Inventory When focused on controlling inventory, Revenue Management is mainly concerned with how best to price or allocate capacity. First, a company can discount products in order to increase volume. By lowering prices on products, a company can overcome weak demand and gain market share, which ultimately increases revenue so long as each product sells for more than its marginal cost. On the other hand, in situations where demand is strong for a product but the threat of cancellations looms (e.g. hotel rooms or airline seats), firms often overbook in order to maximize revenue from full capacity. Overbooking’s focus is increasing the total volume of sales in the presence of cancellations rather than optimizing customer mix. Marketing Price promotion allow companies to sell higher volumes by temporarily decreasing the price of their products. Revenue Management techniques measure customer responsiveness to promotions in order
- 2. to strike a balance between volume growth and profitability. An effective promotion helps maximize revenue when there is uncertainty about the distribution of customer willingness to pay. When a company’s products are sold in the form of long-term commitments, such as internet or telephone service, promotions help attract customers who willthen commit to contracts and produce revenue over a long time horizon. When this occurs, companies must also strategize their promotion roll-off policies; they must decide when to begin increasing the contract fees and by what magnitude to raise the fees in order to avoid losing customers. Revenue Management optimization proves useful in balancing promotion roll-off variables in order to maximize revenue while minimizing churn. Channels Revenue Management through channels involves strategically driving revenue through different distribution channels. Different channels may represent customers with different price sensitivities. For example, customers who shop online are usually more price sensitive than customers who shop in a physical store. Different channels often have different costs and margins associated with those channels. When faced with multiple channels to retailers and distributors, Revenue Management techniques can calculate appropriate levels of discounts for companies to offer distributors through opaque channels to push more products without losing integrity with respect to public perception of quality. The Revenue Management Process Data Collection The Revenue Management process begins with data collection. Relevant data is paramount to a Revenue Management System’s capability to provide accurate, actionable information. A system must collect and store historical data for inventory, prices, demand, and other causal factors. Any data that reflects the details of products offered, their prices, competition, and customer behavior must be collected, stored, and analyzed. In some markets, specialized data collection methods have rapidly emerged to service their relevant sector, and sometimes have even become a norm. In the European Union for example, the European Commission makes sure businesses and governments stick to EU rules on fair competition, while still leaving space for innovation, unified standards, and the development of small businesses. To support this, third party sources are utilized to collect data and make only averages available for commercialpurposes, such as is the case with the hotel sector – in Europe [23] and the Middle East & North Africa region,[24] where key operating indicators are monitored, such as Occupancy Rate (OR), Average Daily Rate (ADR) and Revenue per Available Room (RevPAR). Data is supplied directly by hotel chains and groups (as well as independent properties) and benchmark averages are produced by direct market (competitive set) or wider macro market. This data is also utilized for financial reporting, forecasting trends and development purposes. Information about customer behavior is a valuable asset that can reveal consumer behavioral patterns, the impact of competitors’ actions, and other important market information. This information is crucial to starting the Revenue Management process. Segmentation After collecting the relevant data, market segmentation is the key to market-based pricing and revenue maximization. Success hinges on the ability to segment customers into similar groups based on a calculation of price responsiveness of customers to certain products based upon the circumstances of time and place. Revenue Management strives to determine the value of a product to a very narrow micro-market at a specific moment in time and then chart customer behavior at the margin to determine the maximum obtainable revenue from those micro-markets.[1] Useful tools such as Cluster Analysis allow Revenue Managers to create a set of data-driven partitioning techniques that gather interpretable groups of objects together for consideration. Market segmentation based upon customer behavior is essential to the next step, which is forecasting demand associated with the clustered segments.
- 3. Forecasting Revenue Management requires forecasting various elements such as demand, inventory availability, market share, and total market. Its performance depends critically on the quality of these forecasts. Forecasting is a critical task of Revenue Management and takes much time to develop, maintain, and implement. Quantity-based forecasts, which use time-series models, booking curves, cancellation curves, etc., project future quantities of demand, such as reservations or products bought. Price-based forecasts seek to forecast demand as a function of marketing variables, such as price or promotion. These involve building specialized forecasts such as market response models or cross- price elasticity estimates to predict customer behavior at certain price points. By combining these forecasts with calculated price sensitivities and price ratios, a Revenue Management System can then quantify these benefits and develop price optimization strategies to maximize revenue. Optimization While forecasting suggests what customers are likely to do, optimization suggests how a firm should respond. Often considered the pinnacle of the Revenue Management process, optimization is about evaluating multiple options on how to sell your product and to whom to sell your product.[1] Optimization involves solving two important problems in order to achieve the highest possible revenue. The first is determining which objective function to optimize. A business must decide between optimizing prices, total sales, contribution margins, or even customer lifetime values. Secondly, the business must decide which optimization technique to utilize. For example, many firms utilize linear programming, a complex technique for determining the best outcome from a set of linear relationships, to set prices in order to maximize revenue. Regression analysis, another statistical tool, involves finding the ideal relationship between several variables through complex models and analysis. Discrete choice models can serve to predict customer behavior in order to target them with the right products for the right price. Tools such as these allow a firm to optimize its product offerings, inventory levels, and pricing points in order to achieve the highest revenue possible. Dynamic Re-evaluation Revenue Management requires that a firm must continually re-evaluate their prices, products, and processes in order to maximize revenue. In a dynamic market, an effective Revenue Management System constantly re-evaluates the variables involved in order to move dynamically with the market. As micro-markets evolve, so must the strategy and tactics of Revenue Management adjust. Revenue Management in an Organization Revenue Management’s fit within the organizational structure depends on the type of industry and the company itself. Some companies place Revenue Management teams within Marketing because marketing initiatives typically focus on attracting and selling to customers. Other firms dedicate a section of Finance to handle Revenue Management responsibilities because of the tremendous bottom line implications. Some companies have elevated the position of Chief Revenue Officer, or CRO, to the senior management level. This position typically oversees functions like sales, pricing, new product development, and advertising and promotions. A CRO in this sense would be responsible for all activities that generate revenue and directing the company to become more “revenue-focused. Supply Chain Management and Revenue Management have many natural synergies. Supply chain management (SCM) is a vital process in many companies today and several are integrating this process with a Revenue Management System. On one hand, supply chain management often focuses on filling current and anticipated orders at the lowest cost, while assuming that demand is primarily exogenous. Conversely, Revenue Management generally assumes costs and sometimes capacity are fixed and instead looks to set prices and customer allocations that maximize revenue given these constraints. Acompany that has achieved excellence in Supply Chain Management and Revenue
- 4. Management individually may have many opportunities to increase profitability by linking their respective operational focus and customer-facing focus together. Business Intelligence platforms have also become increasingly integrated with the Revenue Management process. These platforms, driven by data mining processes, offer a centralized data and technology environment that delivers business intelligence by combining historical reporting and advanced analytics to explain and evaluate past events, deliver recommended actions and eventually optimize decision-making. Not synonymous with Customer Relationship Management (CRM), Business intelligence generates proactive forecasts, whereas CRM strategies track and document a company’s current and past interactions with customers. Data mining this CRM information, however, can help drive a business intelligence platform and provide actionable information to aid decision- making. Developing Industries The ability for Revenue Management to optimize price based on forecasted demand, price elasticity and competitive rates has incredible benefits, and many companies are rushing to develop their own Revenue Management capabilities. Many industries are beginning to embrace Revenue Management and apply its principles to their business processes: Financial Services – offer a wide range of products to a wide range of customers. Banks have applied segmented pricing tactics to loan holders, often utilizing heavy amounts of data and modeling to project interest rates based on how much a customer is willing to pay.[26] Media/Telecom – a promotion-driven industry often focused on attracting customers with discounted plans and then retaining them at higher price points. Businesses in this industry often face regulatory constraints, demand volatility, and sales through multiple channels to both business and consumer segments. Revenue Management can help these companies understand micro-markets and forecast demand in order to optimize advertising sales and long-term contracts. Distributors – face a complex environment that often includes thousands of individual SKUs with several different product lifecycles. Each distributor must account for factors such as channel conflict, cross-product cannibalization, and competitive actions. Revenue Management has proved useful to distributors in promotion analysis and negotiated contracts. Medical Products and Services – deal with large fluctuations in demand depending on time of day and day of week. Hospital surgeries are often overflowing on weekday mornings but sit empty and underutilized on the weekend. Hospitals may experiment with optimizing their inventory of services and products based on different demand points. Additionally, Revenue Management techniques allow hospitals to mitigate claim underpayments and denials, thus preventing significant revenue leakage.[29] MKG Group’s HotelCompSet performance indicators in Europe
- 5. Hotel and Hospitality services – daily revenue or yield management strategies are a popular practice within the hotel sector, particularly prominent in mature and large hotel markets such as in Western Europe and the North America. Key operating indicators Occupancy Rate (OR), Average Daily Rate (ADR) and Revenue per Available Room (RevPAR) are tracked using third party sources to follow direct competitor set averages in demand and price, thereby indicating penetration rate and performance index.[30] Wider or macro market averages are also monitored. Since the hotel industry is cyclic, revenue managers can confidently maneuver supply and demand statistics to reach optimal results.